1 Introduction

This project delves into analyzing ransomware infections using data extracted from the Shodan API. By analyzing real-time data on internet-connected devices, we explore ransomware trends across various countries and cities. Through data visualizations and statistical analysis, we aim to identify geographic hotspots of ransomware activity, comprehend infection patterns, and provide valuable insights for cybersecurity professionals. The project underscores the importance of monitoring and comprehending ransomware incidents to enhance global cyber defenses.

1.1 Shodan API Overview

The Shodan API, a powerful tool for searching and retrieving data on internet-connected devices, provides information about devices’ locations, services, vulnerabilities, and more. In this project, the API is used to analyze global trends and patterns of ransomware infections.

2 Data Analysis of Ransomware Infections

This section analyzes ransomware infections. It starts with a summary of affected countries and reported incidents. A statistical analysis presents key metrics on infection distribution. The section concludes with a table detailing ransomware incidents by country and city, revealing geographic trends and high-infection areas.

2.1 Ransomware Infections Summary

According to the Shodan dataset, Brazil is the country with the highest number of ransomware infections, with 12 incidents.

A total of 119 ransomware infections have been reported worldwide, affecting 41 countries!

2.1.1 Statistical Analysis

  • The average number of ransomware infections per country is 2.9
  • The median number of ransomware infections per country is 1
  • The standard deviation of ransomware infections per country is 3.09

2.2 Table of Ransomware Infections by Country and City

This comprehensive table offers a detailed breakdown of ransomware infection rates across various countries and cities. It presents country and city names alongside the corresponding number of ransomware incidents, making it easy to compare regions. This table serves as a crucial reference point for understanding global ransomware trends and identifying areas where cyber defenses may need reinforcement.

Distribution of Ransomware Infections by Country and City
Country City Number of Infections
1082 Germany Frankfurt am Main 5
2204 Russian Federation Moscow 4
1513 Turkey Istanbul 3
2676 Czechia Prague 3
3057 Mexico Santiago de Querétaro 3
3080 Brazil São Paulo 3
3125 China Shanghai 3
322 Spain Barcelona 2
529 Turkey Bursa 2
959 Germany Düsseldorf 2
1351 United States Herndon 2
1719 Ukraine Kyiv 2
2014 Brazil Manaus 2
2353 Germany Nürnberg 2
3001 Chile Santiago 2
3166 China Shenzhen 2
3402 Uzbekistan Tashkent 2
3549 Mexico Villahermosa 2
17 Ghana Accra 1
61 Kazakhstan Almaty 1
121 United States Altamonte Springs 1
128 Brazil Aracruz 1
169 Brazil Araranguá 1
244 United States Ashburn 1
266 Kazakhstan Astana 1
337 China Beijing 1
374 Brazil Boa Esperança 1
425 France Bourg-en-Bresse 1
455 Belarus Brest 1
546 Egypt Cairo 1
581 Canada Calgary 1
654 United States Cedar Grove 1
665 China Chengdu 1
721 Moldova, Republic of Chisinau 1
747 China Chongqing 1
780 Argentina Comodoro Rivadavia 1
830 Colombia Cúcuta 1
900 United States Des Moines 1
905 Bangladesh Dhaka 1
1000 Germany Falkenstein 1
1034 China Foshan 1
1108 Argentina Godoy Cruz 1
1153 Brazil Goiânia 1
1190 Argentina Haedo 1
1271 Viet Nam Hanoi 1
1285 Finland Helsinki 1
1394 Viet Nam Ho Chi Minh City 1
1412 India Hyderābād 1
1461 Pakistan Islamabad 1
1522 Brazil Itajaí 1
1592 South Africa Johannesburg 1
1635 Taiwan Kaohsiung 1
1658 India Kolkata 1
1747 Nigeria Lagos 1
1802 United States Lee’s Summit 1
1832 Peru Lima 1
1875 Portugal Lisbon 1
1921 Spain Madrid 1
1964 Turkey Maltepe 1
1970 Bahrain Manama 1
2060 Colombia Manizales 1
2101 Colombia Medellín 1
2171 United States Mercerville 1
2232 India Mumbai 1
2286 Russian Federation Novyy Urengoy 1
2319 Mexico Nuevo Laredo 1
2401 Mexico Ojuelos de Jalisco 1
2438 Japan Osaka 1
2471 Czechia Ostrava 1
2513 Denmark Otterup 1
2569 Panama Panamá 1
2610 Panama Panama City 1
2647 Mexico Piedras Negras 1
2729 Mexico Puebla 1
2776 Poland Radom 1
2827 United States Rancho Santa Margarita 1
2855 Pakistan Rawalpindi 1
2875 Brazil Rio de Janeiro 1
2942 Russian Federation Saint Petersburg 1
2991 United States Santa Fe Springs 1
3231 Singapore Singapore 1
3261 Macedonia, Republic of Skopje 1
3286 Bulgaria Sofia 1
3360 United States Tacoma 1
3408 Brazil Toledo 1
3479 Spain Tortosa 1
3486 Argentina Villa Sarmiento 1
3602 Spain Villanueva de la Cañada 1
3629 Lithuania Vilnius 1
3682 Singapore Woodlands 1
3722 Serbia Zrenjanin 1

3 Data Visualization of Ransomware Infections

This section visualizes ransomware infection patterns globally. It maps incidents at country and city levels using Shodan API data, highlighting affected regions and trends. An interactive map lets users zoom in and examine infection details, making it useful for cybersecurity professionals and researchers.

3.1 Exploring Ransomware Hotspots

This data visualization explores the global distribution of ransomware infections, focusing on the geographical hotspots by country and city. Using data from the Shodan API, the map highlights areas with the highest concentrations of ransomware incidents, shedding light on trends and patterns in cyberattacks. By mapping ransomware infections based on real-time data, the visualization provides insights into which regions are most affected and allows for a better understanding of the geographic spread of these cyber threats. The interactive map enables users to zoom in on specific locations and view detailed information on the number of incidents, cities, and countries impacted, offering valuable insights for cybersecurity professionals and researchers.